Bonobo Optimizer: A New Tool Toward the Global Optimization of Small Atomic Clusters.

In the realm of structural and bonding investigations within chemical systems, elucidating global minimum energy configurations stands as a paramount goal. As the systems increase in size and complexity, this pursuit becomes progressively challenging. Herein, we introduce Bonobo optimizer (BO), a metaheuristic algorithm inspired by the social and reproductive behaviors of bonobos, to the domain of chemical problem solving. Focusing on small carbon clusters, this study systematically evaluates BO's performance, showcasing its robustness and efficiency. Parametric studies highlight the algorithm's adaptability, consistently converging to global minimum structures. Rigorous statistical validation supports the results, and a comparative analysis against established global optimization algorithms underlines BO's superior efficiency. This exploration extends the applicability of BO to the optimization of atomic clusters, providing a promising avenue for future advancements in computational chemistry.

A comparative assessment of two designs of hip stem using rule-based simulation of combined osseointegration and remodelling.

The stem-bone interface of cementless total hip arthroplasty undergoes an adaptive process of bone ingrowth until the two parts become osseointegrated. Another important phenomenon associated with aseptic loosening of hip stem is stress-shielding induced adverse bone remodelling. The objective of this study was to preclinically assess the relative performances of two distinct designs of hip stems by addressing the combined effect of bone remodelling and osseointegration, based on certain rule-based criteria obtained from the literature. Premised upon non-linear finite element analyses of patient-specific implanted femur models, the study attempts to ascertain in silico outcome of the hip stem designs based on an evolutionary interfacial condition, and to further comment on the efficacy of the rule-based technique on the prediction of peri-prosthetic osseointegration. One of the two hip stem models was a trade-off design obtained from an earlier shape optimization study, and the other was based on TriLock stem (DePuy). Both designs predicted similar long-term osseointegration (∼89% surface), although trade-off stem predicted higher post-operative osseointegration. Proximal bone resorption was found higher for TriLock (by ∼110%) as compared to trade-off model. The rule-based technique predicted clinically coherent osseointegration around both stems and appears to be an alternative to expensive mechanobiology-based schemes.

Reporting cell planning-based cellular mobility management using a Binary Artificial Bat algorithm.

This paper attempts to present a novel application of Binary Artificial Bat algorithm for more effective location management in cellular networks. The location management is a mobility management task, which involves tracking of the mobile stations to locate their exact positions so that an incoming call or data can be routed to the intended mobile user. The location management cost comprises of the costs incurred by two processes, namely location registration and location search. This work focuses on network cost optimization, using Binary Artificial Bat algorithm for reporting cell planning strategy, which has not been reported yet. Results of the proposed algorithm have been compared with that of Binary Particle Swarm Optimization (BPSO) and Binary Differential Evolution (BDE) for some reference and realistic networks. The proposed approach is found to perform as good as other state-of-art techniques reported in the literature in terms of accuracy in solution, but it shows perceptible improvement in convergence speed.